In the rapidly developing network age, video information, as an accurate, efficient, and intuitive multimedia form, has been applied more and more widely.
One of important applications of video information is vision analysis. For example, by performing vision analysis to a monitored video, functions such as automatic alarm, object detection, and object tracking may be implemented; for another example, by vision analysis, a desired image may be retrieved from among mass videos.
In the prior art, a vision analysis task is generally performed at a cloud server, while videos to be subjected to vision analysis are always distributed over a plurality of terminals (e.g., monitoring terminals, etc.). The respective terminals usually need to transmit the videos acquired thereby to respective local servers at their localities which then transmit the videos to the cloud server for the vision analysis task.
However, in practical applications, a relatively large data amount of the videos transmitted to the cloud server will bring a relatively heavy pressure to data transmission as well as to storage at the cloud server.